The Impact of Artificial Intelligence on Motivation for Foreign Language Learning
DOI:
https://doi.org/10.51699/cajlpc.v7i3.1611Keywords:
artificial intelligence, foreign language learning, learner motivation, educational technology, language educationAbstract
Artificial intelligence is increasingly influencing educational practices and language learning worldwide. AI-powered applications provide learners with instant translation, grammar correction, vocabulary support, and personalized feedback, creating new opportunities for foreign language education. At the same time, concerns have emerged regarding whether the growing integration of AI may reduce individuals' motivation to learn foreign languages independently. This study explores public perceptions of this issue through an online poll involving 47 respondents. The findings reveal that most participants do not believe that AI will substantially reduce interest in foreign language learning. The results suggest that language learning continues to be valued for communication, cultural understanding, academic development, and professional growth despite rapid technological advances. The study contributes to ongoing discussions concerning the role of artificial intelligence in language education and learner motivation.
References
A. Dehghan, “Empowering autonomy in language learning: The transformative potential of data-driven learning (DDL) in higher education,” in Emancipatory Education Without Boundaries in the Age of Neoliberalism, Artificial Intelligence and Digital Learning Platforms, M. J. Day, Ed. Cham, Switzerland: Palgrave Macmillan, 2025.
R. Godwin-Jones, “Emerging technologies: Artificial intelligence and language learning,” Language Learning & Technology, vol. 25, no. 3, pp. 5–15, 2021.
W. Holmes, M. Bialik, and C. Fadel, Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston, MA, USA: Center for Curriculum Redesign, 2022.
E. Kasneci et al., “ChatGPT for good? On opportunities and challenges of large language models for education,” Learning and Individual Differences, vol. 103, p. 102274, 2023.
L. Kohnke, B. L. Moorhouse, and D. Zou, “ChatGPT for language teaching and learning,” RELC Journal, vol. 54, no. 2, pp. 537–550, 2023.
J. N. Mirzoyev, “Translation of phraseological units from Tajik into English: A linguocultural approach,” in Innovative Methods in Foreign Language Teaching: Global Trends and the Experience of Silk Road Universities, vol. 1, pp. 1399–1403, 2026.
O. Zawacki-Richter, V. I. Marín, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education,” International Journal of Educational Technology in Higher Education, vol. 16, no. 1, p. 39, 2019.
P. Granger, “Data-driven learning and its applications in language teaching,” System, vol. 29, no. 4, pp. 537–546, 2001.
F. Levy, “Computers and language learning: Context and conceptualization,” Oxford, U.K.: Oxford University Press, 1997.
M. Warschauer and D. Healey, “Computers and language learning: An overview,” Language Teaching, vol. 31, no. 2, pp. 57–71, 1998.
H. Reinders and P. Hubbard, “CALL and learner autonomy: Affordances and constraints,” in Contemporary Computer-Assisted Language Learning, London, U.K.: Bloomsbury, 2013.
N. Schmitt, Vocabulary in Language Teaching. Cambridge, U.K.: Cambridge University Press, 2000.
G. Cook, Translation in Language Teaching. Oxford, U.K.: Oxford University Press, 2010.
D. Crystal, Language and the Internet, 2nd ed. Cambridge, U.K.: Cambridge University Press, 2006.
J. Egbert and E. Hanson-Smith, CALL Environments: Research, Practice, and Critical Issues. Alexandria, VA, USA: TESOL, 1999.
